• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1465-1473
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• 2006

In this paper, we present an approach for facial expression recognition using Active Shape Models(ASM) and a state-based model in image sequences. Given an image frame, we use ASM to obtain the shape parameter vector of the model while we locate facial feature points. Then, we can obtain the shape parameter vector set for all the frames of an image sequence. This vector set is converted into a state vector which is one of the three states by the state-based model. In the classification step, we use the k-NN with the proposed similarity measure that is motivated on the observation that the variation-regions of an expression sequence are different from those of other expression sequences. In the experiment with the public database KCFD, we demonstrate that the proposed measure slightly outperforms the binary measure in which the recognition performance of the k-NN with the proposed measure and the existing binary measure show 89.1% and 86.2% respectively when k is 1.

• Journal of Fashion Business
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• v.13 no.3
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• pp.12-24
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• 2009

This paper aims to investigate if a total of 266 college students from Yanbian, China, and Korea's Jeonnam Province are satisfied with their face and body type, and to find out an image-development method, depending on body characteristics. For this, a questionnaire survey using the 5-point Likert Scale was conducted, and an SPSS program has been used for data analysis. Besides the descriptive analysis, crosstab analysis, t-verification, and frequency analysis have been conducted. As body shape, posture, costume, accessories and makeup play an important role in image formation, this paper intends to form positive ego through exact awareness of the body shape by providing base data to a set image-development strategy. Then, the result has turned out as follows: First, in terms of the body index (i.e., Rohrer index), both Korea's Jeonnam Province and China's Yanbian college students were included in a category of the mean value. In terms of satisfaction with their body shape, on the contrary, China's China's Yanbian college students were higher than Korea's Jeonnam Province college students. Second, male China's Yanbian college students were slightly higher than female China's Yanbian college students in terms of satisfaction with their facial shape. However, the male students showed no big interest in facial care. Third, in terms of facial shape, an egg-shaped face was the most preferred in both China's Yanbian and Korea's Jeonnam Province college students, followed by an inverted triangle-shaped face in China's Yanbian college students and a diamond-shaped face in Korea's Jeonnam Province college students, showing significant difference ($p{\le}.001$). Even though both college students live in Northeast Asia, their preference on facial shape turned out to greatly differ, which indicates their different social environments. This paper will be helpful in global marketing for college students who are the major consumers in the future as Korean-Chinese exchange increases.

• The Journal of Korea Robotics Society
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• v.8 no.4
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• pp.266-272
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• 2013

Facial feature extraction and tracking are essential steps in human-robot-interaction (HRI) field such as face recognition, gaze estimation, and emotion recognition. Active shape model (ASM) is one of the successful generative models that extract the facial features. However, applying only ASM is not adequate for modeling a face in actual applications, because positions of facial features are unstably extracted due to limitation of the number of iterations in the ASM fitting algorithm. The unaccurate positions of facial features decrease the performance of the emotion recognition. In this paper, we propose real-time facial feature extraction and tracking framework using ASM and LK optical flow for emotion recognition. LK optical flow is desirable to estimate time-varying geometric parameters in sequential face images. In addition, we introduce a straightforward method to avoid tracking failure caused by partial occlusions that can be a serious problem for tracking based algorithm. Emotion recognition experiments with k-NN and SVM classifier shows over 95% classification accuracy for three emotions: "joy", "anger", and "disgust".

• Journal of Sasang Constitutional Medicine
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• v.29 no.2
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• pp.95-103
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• 2017

Objectives This study was aimed to analyze characteristics of facial shapes in adult women by sasang constitution using hyungsang classification. Methods Using a digital camera, we took a picture of 1,011 women who participated in clinical study on menstrual pain and acquired their 3D facial images with a face-only scanner. They filled out SSCQ-P(sasang constitution questionnaire for patient) for the diagnosis of sasang constitution. Based on the above photographs and 3D images, one of the hyungsang medicine specialist diagnosed according to five diagnostic criteria. The sasang constitution was diagnosed by referring to questionnaires and photographs. Frequency analysis was performed using the statistical analysis system version 9.4 and chi-square test was performed for validity evaluation. Results In taeeumin, the wide face shape(n=261, 74.36%) was much more than the narrow shape(n=90, 25.64%) and the convex face profile(n=164, 85.86%) was much more than the concave profile(n=27, 14.14%). Regardless of sasang constitution, angular face shape(n=501, 50%) was the most, followed by oval shape(n=317, 31.64%). Subjects with big ears(n=291, 29.19%) were the most, while big eyes(n=104, 10.43%) were the least. Subjects with eyes and nose tip upward(n=615, 78.05%) were the most, while eyes and nose tip downward(n=22, 2.79%) were the least. Conclusions Most Korean adult women have angular face, such as square or diamond, with slanted eyes and upturned nose. Taeeumin women have wide facial shape and convex profile.

• Journal of the Semiconductor & Display Technology
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• v.15 no.2
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• pp.61-65
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• 2016

Facial feature detection is a fundamental function in the field of computer vision such as security, bio-metrics, 3D modeling, and face recognition. There are many algorithms for the function, active shape model is one of the most popular local texture models. This paper addresses issues related to face detection, and implements an efficient extraction algorithm for extracting the facial feature points to use on iOS platform. In this paper, we extend the original ASM algorithm to improve its performance by four modifications. First, to detect a face and to initialize the shape model, we apply a face detection API provided from iOS CoreImage framework. Second, we construct a weighted local structure model for landmarks to utilize the edge points of the face contour. Third, we build a modified model definition and fitting more landmarks than the classical ASM. And last, we extend and build two-dimensional profile model for detecting faces within input images. The proposed algorithm is evaluated on experimental test set containing over 500 face images, and found to successfully extract facial feature points, clearly outperforming the original ASM.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.16.1-164
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• 1998

This paper describes Facial Expression Explorer to search for the components of a facial expression and to map the expression to other expressionless figures like a robot, frog, teapot, rabbit and others. In general, it is a time-consuming and laborious job to create a facial expression manually, especially when the facial expression must personify a well-known public figure or an actor. In order to extract a blending ratio from facial images automatically, the Facial Expression Explorer uses Networked Genetic Algorithm(NGA) which is a fast method for the convergence by GA. The blending ratio is often used to create facial expressions through shape blending methods by animators. With the Facial Expression Explorer a realistic facial expression can be modeled more efficiently.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.38
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• pp.37.1-37.5
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• 2016

Background: The dimensions and shape of the forehead determine the esthetics of the upper third of the face. Korean young people consider a broad and smooth, rounded forehead more attractive. As a result, frontal augmentation becomes more popular in patients with dentofacial deformities. Various surgical procedures and materials have been used in frontal augmentation surgery, with associated advantages and disadvantages. Silicone is a good candidate for frontal augmentation. The author presents two cases of esthetic frontal augmentation with a prefabricated silicone implant in female patients with dentofacial deformities. Case presentation: In case 1, a 24-year-old female patient underwent frontal augmentation surgery with simultaneous maxillomandibular and zygomatic osteotomies to correct facial asymmetry. A silicone implant was fabricated preoperatively using a positive template stone mold of her forehead. In case 2, a 23-year-old female patient underwent total facial contouring surgery including frontal augmentation for improved facial esthetics. A computed tomography (CT)-guided rapid prototype (RP) model was used to make the silicone implants. The operative procedure was safe and simple, and the silicone implants were reliable for a larger degree of frontal augmentation. Six months later, both patients had recovered from the surgery and were satisfied with their frontal shape and projection. Conclusions: Frontal augmentation with silicone implants can be an effective adjuvant strategy to improve facial esthetics in patients with a flat and narrow forehead who undergo orthognathic reconstruction or total facial contouring surgery.

• Journal of Korea Multimedia Society
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• v.4 no.1
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• pp.67-74
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• 2001

In this paper, we propose a face detection algorithm using the color and shape information in color still images. The proposed algorithm is only applied to chrominance components(Cb and Cr) in order to reduce the variations of lighting condition in YCbCr color space. Input image is segmented by pixels with skin-tone color and then the segmented mage follows the morphological filtering an geometric correction to eliminate noise and simplify the segmented regions in facial candidate regions. Multiple facial regions in input images can be isolated by connected component labeling. Moreover tilting facial regions can be detected by extraction of second moment-based ellipse features.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.10
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• pp.63-71
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• 1996

This paper proposes a method which analyzes facial shape and extracts positions of eyes regardless of the tilt and the size of input iamge. With the extracted feature parameters of facial element by the method, full human faces are recognized by a neural network which BP algorithm is applied on. Input image is changed into binary codes, and then labelled. Area, circumference, and circular degree of the labelled binary image are obtained by using chain code and defined as feature parameters of face image. We first extract two eyes from the similarity and distance of feature parameter of each facial element, and then input face image is corrected by standardizing on two extracted eyes. After a mask is genrated line historgram is applied to finding the feature points of facial elements. Distances and angles between the feature points are used as parameters to recognize full face. To show the validity learning algorithm. We confirmed that the proposed algorithm shows 100% recognition rate on both learned and non-learned data for 20 persons.

• Journal of International Society for Simulation Surgery
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• v.1 no.2
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• pp.57-61
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• 2014

We present a robust 3D facial reconstruction method using a single image generated by face-specific super resolution technique. Based on the several consecutive frames with low resolution, we generate a single high resolution image and a three dimensional facial model based on it. To do this, we apply PME method to compute patch similarities for SR after two-phase warping according to facial attributes. Based on the SRI, we extract facial features automatically and reconstruct 3D facial model with basis which selected adaptively according to facial statistical data less than a few seconds. Thereby, we can provide the facial image of various points of view which cannot be given by a single point of view of a camera.